Resource Management and Performance Analysis of Wireless Communication Networks

Description

With the diversification of Internet services and the increase in mobile users, efficient management of network resources has become an extremely important issue in the field of wireless communication networks (WCNs). Adaptive resource management is an effective tool for improving the economic efficiency of WCN systems as well as network design and construction, especially in view of the surge in mobile device demands. This book presents modelling methods based on queueing theory and Markov processes for a wide variety of WCN systems, as well as precise and approximate analytical solution methods for the numerical evaluation of the system performance. This is the first book to provide an overview of the numerical analyses that can be gleaned by applying queueing theory, traffic theory and other analytical methods to various WCN systems. It also discusses the recent advances in the resource management of WCNs, such as broadband wireless access networks, cognitive radio networks, and green cloud computing. It assumes a basic understanding of computer networks and queueing theory, and familiarity with stochastic processes is also recommended. The analysis methods presented in this book are useful for first-year-graduate or senior computer science and communication engineering students. Providing information on network design and management, performance evaluation, queueing theory, game theory, intelligent optimization, and operations research for researchers and engineers, the book is also a valuable reference resource for students, analysts, managers and anyone in the industry interested in WCN system modelling, performance analysis and numerical evaluation. Preface Contents Abbreviations List of Figures List of Tables 1 Introduction 1.1 Overview of Wireless Communication Networks 1.1.1 Broadband Wireless Access Networks 1.1.2 Cognitive Radio Networks 1.1.3 Cloud Computing 1.2 Resource Management 1.2.1 Static Spectrum Allocation 1.2.2 Dynamic Spectrum Allocation 1.2.3 Virtualization 1.2.4 Virtual Machine Migration 1.3 Queueing Models and Performance Analyses 1.3.1 Basic and Vacation Queueing Models 1.3.1.1 Basic Queueing Model 1.3.1.2 Performance Measures and Common Definitions 1.3.1.3 Vacation Queueing Model 1.3.2 Queueing Model with Multiple-Class Customers 1.3.3 Matrix-Geometric Solution Method 1.3.3.1 Birth-Death Process 1.3.3.2 Quasi Birth-Death Process 1.3.3.3 Matrix-Geometric Solution Method 1.3.4 Jacobi Iterative Method 1.3.5 Gauss-Seidel Method 1.3.6 Performance Optimization 1.3.6.1 Optimization of System Parameters 1.3.6.2 Nash Equilibrium and Social Optimization 1.4 Organization of This Book Part I Resource Management and Performance Analysis on Broadband Wireless Access Networks 2 Sleep Mode for Power Saving Class Type I 2.1 Introduction 2.2 Working Principle and System Model 2.2.1 Working Principle 2.2.2 System Model 2.3 Performance Analysis 2.4 Performance Measures 2.4.1 System Energy 2.4.2 Average Response Time of Data Packets 2.4.3 System Cost 2.5 Numerical Results 2.6 Conclusion 3 Sleep Mode for Power Saving Class Type II 3.1 Introduction 3.2 Working Principle and System Model 3.2.1 Working Principle 3.2.2 System Model 3.3 Analysis of Busy Cycle 3.3.1 Busy Period in Listening State 3.3.2 Busy Period in Awake State 3.3.3 Time Length of Busy Cycle 3.4 Analysis of Waiting Time 3.4.1 Waiting Time in Listening State 3.4.2 Waiting Time in Awake State 3.4.3 System Waiting Time 3.5 Performance Measures and Numerical Results 3.5.1 Performance Measures 3.5.2 Numerical Results 3.6 Optimal Sleep Window Length 3.7 Conclusion 4 Sleep Mode for Power Saving Class Type III 4.1 Introduction 4.2 Working Principle and System Model 4.2.1 Working Principle 4.2.2 System Model 4.3 Performance Analysis 4.3.1 Number of Data Packets and Batches 4.3.2 Queue Length and Waiting Time 4.3.3 Busy Cycle 4.4 Performance Measures 4.4.1 Handover Rate 4.4.2 Energy Saving Rate 4.4.3 System Utilization 4.4.4 Average Response Time 4.5 Numerical Results 4.6 Conclusion 5 Bernoulli Arrival-Based Sleep Mode in WiMAX 2 5.1 Introduction 5.2 Working Principle of Sleep Mode in IEEE 802.16m 5.3 System Model and Performance Analysis 5.3.1 System Model 5.3.2 Performance Analysis 5.4 Numerical Results 5.5 Conclusion 6 Markovian Arrival-Based Sleep Mode in WiMAX 2 6.1 Introduction 6.2 System Model and Performance Analysis 6.2.1 System Model 6.2.2 Number of Data Packets 6.2.3 Busy Cycle 6.3 Performance Measures and Optimization 6.3.1 Performance Measures 6.3.2 Performance Optimization 6.4 Numerical Results 6.5 Conclusion 7 Two-Stage Vacation Queue-Based Active DRX Mechanism in an LTE System 7.1 Introduction 7.2 Enhanced Energy Saving Strategy 7.3 System Model and Performance Analysis 7.3.1 System Model 7.3.2 Busy Period 7.3.3 Queue Length and Waiting Time 7.3.4 Busy Cycle 7.3.5 Performance Measures 7.4 Numerical Results and Performance Optimization 7.4.1 Numerical Results 7.4.2 Performance Optimization 7.5 Conclusion 8 Multiple-Vacation Queue-Based Active DRX Mechanism in an LTE System 8.1 Introduction 8.2 Enhanced Active DRX Mechanism 8.3 System Model and Performance Analysis 8.3.1 System Model 8.3.2 Transition Probability Sub-Matrices for Case I 8.3.3 Transition Probability Sub-Matrices for Case II 8.3.4 Performance Measures 8.4 Numerical Results and Performance Optimization 8.4.1 Numerical Results 8.4.2 Performance Optimization 8.5 Conclusion Part II Resource Management and Performance Analysis on Cognitive Radio Networks 9 Channel Aggregation Strategy with Perfect-Sensing Results 9.1 Introduction 9.2 Channel Aggregation Strategy and System Model 9.2.1 Channel Aggregation Strategy 9.2.2 System Model 9.3 Performance Analysis and Numerical Results 9.3.1 Steady-State Distribution 9.3.2 Performance Measures and Analysis of System Cost 9.3.3 Numerical Results 9.4 Analysis of Admission Fee 9.4.1 Nash Equilibrium Behavior 9.4.2 Socially Optimal Behavior 9.4.3 Pricing Policy 9.5 Conclusion 10 Spectrum Reservation Strategy with Retrial Feedback and Perfect-Sensing Results 10.1 Introduction 10.2 Spectrum Reservation Strategy and System Model 10.2.1 Spectrum Reservation Strategy 10.2.2 System Model 10.3 Performance Analysis and Numerical Results 10.3.1 Performance Analysis 10.3.2 Performance Measures 10.3.3 Numerical Results 10.4 Performance Optimization 10.4.1 Analysis of System Cost 10.4.2 Optimization of System Parameters 10.5 Conclusion 11 Opportunistic Spectrum Access Mechanism with Imperfect Sensing Results 11.1 Introduction 11.2 Opportunistic Spectrum Access Mechanism and System Model 11.2.1 Activity of PU Packets 11.2.2 Activity of SU Packets 11.2.3 System Model 11.3 Performance Analysis 11.3.1 Mistake Detections and False Alarms 11.3.2 Transition Probability Matrix 11.4 Performance Measures and Numerical Results 11.4.1 Performance Measures 11.4.2 Numerical Results 11.5 Analysis of Admission Fee 11.5.1 Behaviors of Nash Equilibrium and Social Optimization 11.5.2 Pricing Policy 11.6 Conclusion 12 Mini-Slotted Spectrum Allocation Strategy with Imperfect Sensing Results 12.1 Introduction 12.2 Mini-Slotted Spectrum Allocation Strategy and System Model 12.2.1 Mini-Slotted Spectrum Allocation Strategy 12.2.2 System Model 12.3 Performance Analysis 12.3.1 Transition Probability Matrix 12.3.2 Steady-State Distribution 12.4 Performance Measures and Numerical Results 12.4.1 Performance Measures 12.4.2 Numerical Results 12.5 Performance Optimization 12.6 Conclusion 13 Channel Reservation Strategy with Imperfect Sensing Results 13.1 Introduction 13.2 Channel Reservation Strategy and System Model 13.2.1 Channel Reservation Strategy 13.2.2 System Model 13.3 Performance Analysis and TLBO-SOR Algorithm 13.3.1 Performance Analysis 13.3.2 TLBO-SOR Algorithm 13.4 Performance Measures and Numerical Results 13.4.1 Performance Measures 13.4.2 Numerical Results 13.5 Conclusion 14 Energy Saving Strategy in CRNs Based on a Priority Queue with Single Vacation 14.1 Introduction 14.2 Energy Saving Strategy and System Model 14.2.1 Energy Saving Strategy 14.2.2 System Model 14.3 Performance Analysis and Numerical Results 14.3.1 Performance Analysis 14.3.2 Performance Measures 14.3.3 Numerical Results 14.4 Analysis of Admission Fee 14.4.1 Behaviors of Nash Equilibrium and Social Optimization 14.4.2 Pricing Policy 14.5 Conclusion 15 Energy Saving Strategy in CRNs Based on a Priority Queue with Multiple Vacations 15.1 Introduction 15.2 Energy Saving Strategy and System Model 15.2.1 Energy Saving Strategy 15.2.2 System Model 15.3 Performance Analysis 15.4 Performance Measures and Numerical Results 15.4.1 Performance Measures 15.4.2 Numerical Results 15.5 Performance Optimization 15.5.1 Analysis of System Cost 15.5.2 Optimization of System Parameters 15.6 Conclusion Part III Resource Management and Performance Analysis on Cloud Computing 16 Speed Switch and Multiple-Sleep Mode 16.1 Introduction 16.2 Virtual Machine Scheduling Strategy and System Model 16.2.1 Virtual Machine Scheduling Strategy 16.2.2 System Model 16.3 Performance Analysis 16.3.1 Transition Rate Matrix 16.3.2 Steady-State Distribution 16.4 Performance Measures and Numerical Results 16.4.1 Performance Measures 16.4.2 Numerical Results 16.5 Performance Optimization 16.6 Conclusion 17 Virtual Machine Allocation Strategy 17.1 Introduction 17.2 Virtual Machine Allocation Strategy and System Model 17.2.1 Virtual Machine Allocation Strategy 17.2.2 System Model 17.3 Performance Analysis 17.3.1 Transition Rate Matrix 17.3.2 Steady-State Distribution 17.4 Performance Measures and Numerical Results 17.4.1 Performance Measures 17.4.2 Numerical Results 17.5 Performance Optimization 17.6 Conclusion 18 Clustered Virtual Machine Allocation Strategy 18.1 Introduction 18.2 Clustered Virtual Machine Allocation Strategy and System Model 18.2.1 Clustered Virtual Machine Allocation Strategy 18.2.2 System Model 18.3 Performance Analysis 18.3.1 Transition Rate Matrix 18.3.2 Steady-State Distribution 18.4 Performance Measures and Numerical Results 18.4.1 Performance Measures 18.4.2 Numerical Results 18.5 Performance Optimization 18.6 Conclusion 19 Pricing Policy for Registration Service 19.1 Introduction 19.2 Cloud Architecture and System Model 19.2.1 Cloud Architecture 19.2.2 System Model 19.3 Performance Analysis 19.3.1 Transition Rate Matrix 19.3.2 Steady-State Distribution 19.4 Performance Measures and Numerical Results 19.4.1 Performance Measures 19.4.2 Numerical Results 19.5 Analysis of Registration Fee 19.5.1 Behaviors of Nash Equilibrium and Social Optimization 19.5.2 Pricing Policy 19.6 Conclusion 20 Energy-Efficient Task Scheduling Strategy 20.1 Introduction 20.2 Energy-Efficient Task Scheduling Strategy and System Model 20.2.1 Energy-Efficient Task Scheduling Strategy 20.2.2 System Model 20.3 Performance Analysis 20.3.1 Transition Rate Matrix 20.3.2 Steady-State Distribution 20.4 Performance Measures and Numerical Results 20.4.1 Performance Measures 20.4.2 Numerical Results 20.5 Performance Optimization 20.6 Conclusion 21 Energy-Efficient Virtual Machine Allocation Strategy 21.1 Introduction 21.2 Energy-Efficient Virtual Machine Allocation Strategy and System Model 21.2.1 Energy-Efficient Virtual Machine Allocation Strategy 21.2.2 System Model 21.3 Performance Analysis 21.3.1 Transition Rate Matrix 21.3.2 Steady-State Distribution 21.4 Performance Measures and Numerical Results 21.4.1 Performance Measures 21.4.2 Numerical Results 21.5 Analysis of Admission Fee 21.5.1 Behaviors of Nash Equilibrium and Social Optimization 21.5.2 Pricing Policy 21.6 Conclusion References Index